Predicting Warranty Expense Using Reliability Analysis Methods
Instructor:
Steven Wachs
Product ID: 702237
- Duration: 75 Min
Why Should You Attend:
Manufacturers design and develop products based on an expected product lifetime. Many manufacturers conduct extensive reliability testing to minimize the risk that products will fail prematurely. Despite these efforts, unexpected failures occur due to design flaws, manufacturing process changes, or a misunderstanding of the product use environment. Premature failures alienate customers and significantly impair brand and company reputations. Failure data may be easily modeled to forecast future failures and identify emerging issues that present financial risks to the organization.
This 60-minute presentation will show how you can use failure data to predict expected future failures, proactively drive quality and reliability improvement and react quickly to emerging issues.
Areas Covered in the Webinar:
- Modeling Time-To-Failure Data.
- Predicting Future Failures.
- Developing a Warranty Forecast.
- Accounting for Model Uncertainty.
- Identifying Non-Homogeneous Groups.
- Handling Non-Homogenous Groups (e.g. Model Revisions / Design Levels).
Who Will Benefit:
- Product Development Personnel
- Product Engineers
- Managers
- Executives Finance Staff
- Reliability Professionals
- Quality Personnel
Steven Wachs
Principal Statistician, Integral Concepts, Inc
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. He has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.
Mr. Wachs is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Mr. Wachs regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.
He has an M.A. in Applied Statistics from the University of Michigan, an M.B.A, Katz Graduate School of Business from the University of Pittsburgh, 1992, and a B.S., Mechanical Engineering from the University of Michigan.
More Training By Experts
- Applying Statistical Process Control Effectively
- Estimating Reliability Performance with Accelerated Life Tests
- Predicting Product Life Using Reliability Analysis Methods
- Making Data Driven Decisions using Statistical Hypothesis Testing
- Acceptance Sampling Plans for Process Validation and Production Lot Monitoring
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